القائمة
Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism. Use when strategy_drafts/*.yaml exists and needs quality gate before pipeline export. Outputs PASS/REVISE/REJECT verdicts with confidence scores.
Orchestrate the full edge research pipeline from candidate detection through strategy design, review, revision, and export. Use when coordinating multi-stage edge research workflows end-to-end.
Convert Kanchi-style dividend investing into a repeatable US-stock operating procedure. Use when users ask for かんち式配当投資, dividend screening, dividend growth quality checks, PERxPBR adaptation for US sectors, pullback limit-order planning, or one-page stock memo creation. Covers screening, deep dive, entry planning, and post-purchase monitoring cadence.
Validate multi-skill workflows defined in CLAUDE.md by checking skill existence, inter-skill data contracts (JSON schema compatibility), file naming conventions, and handoff integrity. Use when adding new workflows, modifying skill outputs, or verifying pipeline health before release.
This skill should be used when analyzing sector rotation patterns and market cycle positioning. It fetches sector uptrend data from CSV (no API key required) and optionally accepts chart images for supplementary analysis. Use this skill when the user requests sector rotation analysis, cyclical vs defensive assessment, overbought/oversold identification, or market cycle phase estimation. All analysis and output are conducted in English.
Mine Claude Code session logs for skill idea candidates. Use when running the weekly skill generation pipeline to extract, score, and backlog new skill ideas from recent coding sessions.
Screen US stocks using William O'Neil's CANSLIM growth stock methodology. Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum following O'Neil's investment system.
| name | edge-strategy-reviewer |
| description | Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism. Use when strategy_drafts/*.yaml exists and needs quality gate before pipeline export. Outputs PASS/REVISE/REJECT verdicts with confidence scores. |
Deterministic quality gate for strategy drafts produced by edge-strategy-designer.
edge-strategy-designer generates strategy_drafts/*.yamledge-candidate-agent via the pipelineedge-strategy-designer)--drafts-dir or a single --draft file| # | Criterion | Weight | Key Checks |
|---|---|---|---|
| C1 | Edge Plausibility | 20 | Thesis quality, domain terms, mechanism keywords (continuous 50-95) |
| C2 | Overfitting Risk | 20 | 5-tier filter count scoring (90/80/60/40/10), precise threshold penalty |
| C3 | Sample Adequacy | 15 | Continuous scoring from estimated annual opportunities (10-95) |
| C4 | Regime Dependency | 10 | Cross-regime validation |
| C5 | Exit Calibration | 10 | Stop-loss, reward-to-risk |
| C6 | Risk Concentration | 10 | Position sizing limits |
| C7 | Execution Realism | 10 | Volume filter, export consistency |
| C8 | Invalidation Quality | 5 | Signal count and specificity |
# Review all drafts in a directory
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--drafts-dir reports/edge_strategy_drafts/ \
--output-dir reports/
# Single draft review
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--draft reports/edge_strategy_drafts/draft_xxx.yaml \
--output-dir reports/
# JSON output with markdown summary
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--drafts-dir reports/edge_strategy_drafts/ \
--output-dir reports/ \
--format json \
--markdown-summary
# Strict export mode: export-eligible drafts with any warn → REVISE
python3 skills/edge-strategy-reviewer/scripts/review_strategy_drafts.py \
--drafts-dir reports/edge_strategy_drafts/ \
--output-dir reports/ \
--strict-export
Primary output: review.yaml (or review.json)
generated_at_utc: "2026-02-28T12:00:00+00:00"
source:
drafts_dir: "/path/to/strategy_drafts"
draft_count: 4
summary:
total: 4
PASS: 1
REVISE: 2
REJECT: 1
export_eligible: 1
reviews:
- draft_id: "draft_xxx_core"
verdict: "PASS"
confidence_score: 80
export_eligible: true
findings: [...]
revision_instructions: []
references/review_criteria.md — Detailed scoring rubric for C1-C8references/overfitting_checklist.md — Overfitting detection heuristics